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Dual disasters: Seismic evacuation decision-making during COVID-19 lockdown: A case study of Luding earthquake, Sichuan Province

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  • Bahmani, Homa
  • Ao, Yibin
  • Li, Mingyang
  • Yang, Dujuan
  • Wang, Dongpo

Abstract

Although there is a growing body of literature on the COVID-19 pandemic and the implemented strategies that have imposed additional risks in tackling emergencies by increasing socio-economic vulnerabilities, studies on human evacuation behavior during lockdowns are lacking. This paper contributes to evacuation and emergency research by examining seismic evacuation decision-making by surveying the areas affected by the Luding earthquake on 5 September 2022, when most parts of Sichuan province were experiencing strict pandemic restrictions. Using these data and per the emergency evacuation decision-making mechanism, we developed six hierarchical series of logistic regression models. Our major results suggest that 1) Socio-demographic parameters have shown different correlations with the study's dependent variables in each stage of those hierarchical models, 2) Respondents at home at the time of the earthquake were more likely to identify the earthquake risk than those who stayed outdoors; the former group showed less willingness to evacuate, 3) Rural residents have perceived higher earthquake risks than urban residents, and 4) Loss of job, change in income due to COVID-19 restrictions, and difficulty accessing daily supplies during the lockdown affected the residents' risk assessment and evacuation decision-making negatively. Insights into these aspects are expected to contribute to a better understanding of evacuation behavior during double disasters by modifying emergency response regulations and providing the residents with information about emergencies during pandemic restrictions.

Suggested Citation

  • Bahmani, Homa & Ao, Yibin & Li, Mingyang & Yang, Dujuan & Wang, Dongpo, 2023. "Dual disasters: Seismic evacuation decision-making during COVID-19 lockdown: A case study of Luding earthquake, Sichuan Province," Journal of Transport Geography, Elsevier, vol. 110(C).
  • Handle: RePEc:eee:jotrge:v:110:y:2023:i:c:s0966692323000947
    DOI: 10.1016/j.jtrangeo.2023.103622
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